{"id":630845,"url":"https://alion.io/job/d2b-senior-ai-solutions-architect-remote-dayshift","title":"Senior AI Solutions Architect - Remote Dayshift","company":{"id":709562,"name":"Pear Tree","domain":"pear-tree.com","url":"https://alion.io/company/pear-tree","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":70,"open_postings":306,"ghost_share":0.5,"stale_share":0,"repost_share":0.003,"time_to_fill_p50_days":26,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Manila, Philippines"],"countries":["PH"],"hiring_countries":["PH"],"hiring_countries_total":1,"salary":{"min":170000,"max":null,"currency":"PHP","period":"month","gross":null,"usd_annual":32580},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"pgvector","optional":false},{"name":"PHP","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Replit","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-09-02T00:00:00Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-11-11T06:23:42Z","board_verified":true,"closed_at":null,"days_open":70,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":70},"description":"Position : Senior AI Solutions Architect\nSalary : Php 170,000 - 200,000 per month\nWorking Hours & Conditions : New Zealand Hours & Holidays\nEmployment: Full Time - Independent Contractor\nAbout the Role\nThis Senior AI Solutions Architect / CTO has strong relational database modelling, metadata-driven SaaS architecture, and LLM / agentic workflow experience. We are looking for a very senior, hands-on AI-native technical leader who can operate across architecture, solution design, code delivery, code review, and AI-assisted development. This person should be strong enough to contribute to the initial build directly, but also senior enough to help define the engineering standards, architecture patterns, and hiring bar for future developers. This is not a pure architect role and not a pure developer role. We need someone who can bridge both.\nKey Responsibilities\nUnderstand and contribute to the CRM and BI product architecture. \nWork with leadership to shape the technical roadmap. \nTranslate product requirements into secure, scalable, maintainable technical solutions. \nUse AI coding tools such as Claude Code, Cursor, GitHub Copilot, Codex, Replit, or similar to accelerate delivery.\nPersonally contribute to development where required, especially in the early stages. \nReview AI-generated code critically before it reaches production. \nProtect the integrity of multi-tenant architecture, including tenant isolation, role based access control, data security, auditability, and maintainability. \nHelp define coding standards, architecture decision records, delivery patterns, and AI development workflows.\nSupport sprint planning by breaking larger initiatives into technically clear work packages. \nHelp interview and assess future AI developers and QA automation resources. \nAct as a trusted technical counterpart to our internal leadership team. \nRequirements\nSenior full-stack software engineering background. \nStrong relational database design and data modelling experience, including complex entity relationships, lookup relationships, junction objects, field types, referential integrity, indexing, and query performance. \nStrong understanding of CRM-style data models, including accounts, contacts, leads, opportunities, activities, tasks, notes, emails, custom objects, and related records. \nAbility to design metadata-driven data structures where customers can configure objects, fields, layouts, relationships, and workflows without custom code. \nStrong understanding of tenant-scoped data access and the risks of data leakage in a multi tenant SaaS platform. • Strong understanding of AI and LLM application architecture, not only AI-assisted coding. \nExperience or strong working knowledge of agentic workflows, tool calling, retrieval augmented generation, vector databases, embeddings, structured outputs, and AI guardrails. \nAbility to design AI features that can safely reason over CRM records, relationships, documents, emails, tasks, and business workflows. \nAbility to design human-in-the-loop controls, audit logs, permission checks, and approval flows for AI-driven actions.\nPreferred technical experience\nReact and TypeScript. • Python and FastAPI. \nPostgreSQL or other advanced relational databases. \nAdvanced SQL, query optimisation, indexing, joins, and database performance tuning. \nRelational database design, including one-to-many, many-to-many, lookup relationships, junction objects, referential integrity, and schema migrations. \nData modelling for CRM, ERP, workflow, BI, or metadata-driven applications. \nMetadata-driven SaaS architecture where objects, fields, layouts, relationships, permissions, and workflows can be configured dynamically. \nMulti-tenant SaaS platforms, including tenant isolation, tenant-scoped queries, shared versus dedicated data models, and data leakage prevention. \nAuthentication and authorisation frameworks. \nRole-based access control and permission-aware application design. \nAPI architecture and integration design. • Data pipelines and integration architecture. \nEvent-driven architecture and background job processing. \nAutomated testing, CI/CD, and release governance. \nCloud deployment experience. \nVector databases or vector search, such as pgvector, Pinecone, Weaviate, Qdrant, or similar. \nEmbedding models and semantic search. \nLLM orchestration frameworks or patterns. \nAI agent frameworks, tool/function calling, and workflow automation. \nRetrieval-augmented generation architecture. \nSecure AI application design, including tenant-aware retrieval, permission checks, auditability, human-in-the-loop controls, and prevention of cross-tenant data 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